CancerInSilico: An R/Bioconductor package for combining mathematical and statistical modeling to simulate time course bulk and single cell gene expression data in cancer

Bioinformatics techniques to analyze time course bulk and single cell omics data are advancing. The absence of a known ground truth of the dynamics of molecular changes challenges benchmarking their performance on real data. Realistic simulated time-course datasets are essential to assess the perfor...

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Veröffentlicht in:PLoS Comput Biol
Hauptverfasser: Sherman, Thomas D., Kagohara, Luciane T., Cao, Raymon, Cheng, Raymond, Satriano, Matthew, Considine, Michael, Krigsfeld, Gabriel, Ranaweera, Ruchira, Tang, Yong, Jablonski, Sandra A., Stein-O'Brien, Genevieve, Gaykalova, Daria A., Weiner, Louis M., Chung, Christine H., Fertig, Elana J.
Format: Artigo
Sprache:Inglês
Veröffentlicht: Public Library of Science 2019
Schlagworte:
Research Article
Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC6504085/
https://ncbi.nlm.nih.gov/pubmed/31002670
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pcbi.1006935
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